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Discussion (16 Comments)Read Original on HackerNews
The “least worst” representation of the course of events is that their researchers are just jerks, and not behaving in a manner that’s considered acceptable in the research community.
Other alleged scenarios just go downhill from there.
They were surprised another competitor had not wastefully thrown $20 million+ worth of compute at a problem they had no business solving in the first place?
That's reaching, imho.
1. This is not the first time they have done these “hey guys check out this breakthrough!” announcements where others quickly came along and say “hey, not so fast.” (Eg Erdos) So, specifically in maths their reputation is not good.
2. They’re blurring the lines between commercial cutthroat developments and the gentlemen’s code of sorts re what’s acceptable in academic research. They were working from material non-public insights into other research, which is why they even tried to poke at this in the way they did. Doing that without collaborating first was a pretty jerk move no mater how you slice it.
3. There’s still lots of open questions about how novel the solution was and the timing here where this “test” only happened after other researchers say they fed OpenAI models at least part of the solution is a little too convenient to gloss over. OpenAI statements here to date on the matter have been rather fuzzy.
All that combined with OpenAI’s less than stellar reputation on ethics is why folks are reacting the way they are right now.
And that is a good thing! Competition moves us forward much faster than sitting on results to avoid hurting someone's feelings.
Terrence Tao recently published an interesting take that zooms out from the details of the Navier Stokes drama.
Its an interesting observation he makes, because it is not dissimilar from the relatively common phenomenon of one academic lab getting scooped by another lab (usually by coincidence).
A.) The actual steps of the proof, which I assume the AI would provide. B.) People, while working toward a solution, finding novel properties/methods along the way that open new avenues of research + new open problems.
Does B.) actually happen? Would knowing the solution to a problem stymie the process of finding new open questions? I would assume finding a solution may unlock other problems too. So maybe on balance it's not really bad?
I guess in the end, I'm just making the obvious case "the future is uncertain in the face of AI".
I was with you up to “usually by coincidence”.
There’s a long and sordid history in areas of chemistry and areas of biology of holding up a competing paper in review so you can scoop them. I’m sure it exists in physics as well. Certainly biophysics, but probably most subfields.
Often it’s a famous labs that can steamroll review or even just dump the work into PNAS as a “member contribution.”
At least one author of a famous inorganic chemistry textbook was rumored to do this routinely.
And I know of at least one National Academy member who swore off arxiv prepublication after getting scooped.
None of this makes it all right. But plagiarism and academic theft is old and definitely not always accidental.
> Regarding the level of human involvement on our end: although a group of people was involved in our efforts, we collectively had no research-level expertise in fluid dynamics and the Navier-Stokes problem, and therefore were unable to meaningfully contribute to the mathematical content.
https://x.com/SebastienBubeck/status/2097379415747342689
Statement from OpenAI: https://news.ycombinator.com/item?id=49613262
I can read the 2 pages in ~30s or so. How long is the video? 15m? Nah.
Edit: video is 37 minutes
Such a satisfying quote.
Get ready, bag-holders on index-tracking funds... you're about to lose your shirts.
I can't wait to see your short position that will make you rich enough to retire.